How to Use the Corpay One MCP in LangChain
Build payment workflows in LangChain by chaining Corpay One tools directly into your agent's reasoning process.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Corpay One MCP to LangChain
Create your Vinkius account to connect Corpay One to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Chain Corpay One actions in LangChain
Feed your agent a list of tools like `list_payments` or `list_financial_documents` and watch it build a logic path. The output from one call flows into the next without you needing to write manual glue code. Tracing every step in LangSmith shows you exactly how the agent decides to hit the API. You’ll see the latency and the specific arguments passed to `create_new_document` in real time.
Automate vendor management via MCP
Use `list_account_vendors` to get your supplier list directly into your LangChain agent's context. It makes mapping invoices to specific entities instant. Your agent can cross-reference these vendors against incoming documents. It handles the lookup before you even have to glance at the dashboard.
Trace payment data flows
Every tool call is a node in your chain, allowing you to debug how Corpay One data moves through your app. If a `get_payment_details` call fails, you see the exact input that caused the issue. This visibility matters when you're building complex pipelines. You aren't guessing why a payment didn't process; you're looking at the stack trace.
Set up Corpay One MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"transport": "http"pointing to your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Create a ReAct agent
Pass the discovered tools to
create_react_agent()from LangGraph. The agent automatically routes Corpay One tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"corpay-one-mcp": {
"transport": "http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
result = await agent.ainvoke({
"messages": "List recent Corpay One transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Corpay One. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Corpay One MCP in LangChain
Use it with your favorite AI tools
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